• Structural Engineering and Mechanics
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• v.51 no.3
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• pp.377-402
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• 2014

In this study, optimal distribution of springs which supports a cantilever beam is investigated to minimize two objective functions defined. The optimal size and location of the springs are ascertained to minimize the tip deflection of the cantilever beam. Afterwards, the optimization problem of springs is set up to minimize the tip absolute acceleration of the beam. The Fourier Transform is applied on the equation of motion and the response of the structure is defined in terms of transfer functions. By using any structural mode, the proposed method is applied to find optimal stiffness and location of springs which supports a cantilever beam. The stiffness coefficients of springs are chosen as the design variables. There is an active constraint on the sum of the stiffness coefficients and there are passive constraints on the upper and lower bounds of the stiffness coefficients. Optimality criteria are derived by using the Lagrange Multipliers. Gradient information required for solution of the optimization problem is analytically derived. Optimal designs obtained are compared with the uniform design in terms of frequency responses and time response. Numerical results show that the proposed method is considerably effective to determine optimal stiffness coefficients and locations of the springs.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.112-117
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• 2007

In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.412-418
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• 2011

Reliability-based Topology optimization(RBTO) is to get an optimal design satisfying uncertainties of design variables. Although RBTO based on homogenization and density distribution method has been done, RBTO based on BESO has not been reported yet. This study presents a reliability-based topology optimization(RBTO) using bi-directional evolutionary structural optimization(BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying allowable displacement and target reliability index with the above four methods, and then each result is compared with respect to numerical stability and computing time. The results of this study show that the RBTO based on BESO using the four methods can effectively be applied for topology optimization. And it was confirmed that DLSV and ADL had better numerical efficiency than SLSV. ADL and SLSV had better time cost than DLSV. Consequently, ADL method showed the best time efficiency and good numerical stability.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.217-229
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• 2007

In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.71-77
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• 2005

This paper presents a systematic approach which determines the optimal period to minimize performance measure subject to the schedulability constraints of a real-time control system by formulating the scheduling problem as an optimal problem. The performance measure is derived from the summation of end-to-end response times of processed I/Os scheduled by the static cyclic method. The schedulability constraint is specified in terms of allowable resource utilization. At first, a uniprocessor case is considered and then it is extended to a distributed system connected through a communication link, local-inter network, UN. This approach is applied to the design of an automotive body control system in order to validate the feasibility through a real example. By using the approach, a set of optimal periods can easily be obtained without complex and advanced methods such as branch and bound (B&B) or simulated annealing.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.557-562
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• 2004

This paper deals with a robust mixed ${H_2}/{H_{\infty}}$ filter design problem for a nonlinear dynamic system modeled as a T-S fuzzy system. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. A sufficient condition for solvability is given in terms of linear matrix inequality problem which can be efficiently solved using a convex optimization technique. In order to demonstrate the Proposed method, a numerical design example is provided.

• YAKHAK HOEJI
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• v.20 no.1
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• pp.63-69
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• 1976

Prednisolone tablet product design problem was structured as constrained optimization problem and subsequently solved by multiple regression analysis and Lagrangian method of optimixation. Prednisolone was the drug chosen and anhydrous lactose and corn starch were the adjuvants. The effect of anhydrous lactose and corn starch concentrations on tablet hardness, volume, disintegration time and in vitro release rate was studied. The concentrations of anhydrous lactose and corn starch used in this experiment were 30-60 percent and 5-30 percent, respectively. A full second-order (quadratic) model with all possible two-factor interactions was employed. To obtain the values of anhydrous lactose and corn starch which miniumize the in vitro : release time (t$_{60%}$) subject to the constraint on tablet hardness, disintegration time and volume, we solved the Lagrange function. Multiple correlation coefficients for the regression models were correlated at less than 0.05 level and it was found that the optimum concentrations of anhydrous lactose and corn starch were 45 percent and 21 percent, respectively.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1131-1133
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• 1996

In this paper, we consider the mixed $L_1/H_{\infty}$ problems of finding internally stabilizing controllers which minimize the peak-to-peak gain of a certain closed loop transfer function with $H_{\infty}$-norm constraint on other closed loop transfer function(or vise versa). This problem is a useful framework for designing a controller with the norm constraints upon time and frequency domain. We formulate the mixed $L_1/H_{\infty}$ problem as LMI problems by using the reachable set. This paper offers the sufficient condition for the existence of suboptimal state feedback controller, and shows that suboptimal solution can be obtained by solving a finite-dimensional convex optimization and a line search.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.143-151
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• 2010

Automation and robotization has been required in construction for several decades and construction industry has become one of the important research areas in the field of service robotics. Especially in the steel construction, automatic recognition of structural steel members in the stockyard is emphasized. However, since the pose of steel frame in the stockyard is site dependent and also the stockyard is usually in the outdoor environment, it is difficult to determine the pose automatically. This paper adopts the recognition method based on the augmented reality to cope with this problem. Particularly focusing on the light condition of the outdoor environment, we formulated the optimization problem with the constraint and suggested the methodology to evaluate the optimal camera arrangement. From simulation results, sub-optimal solution for the position of the camera can be obtained.

• Journal of Korean Society of Steel Construction
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• v.10 no.4 s.37
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• pp.657-666
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• 1998

This study presents an effective dual algorithm for the optimal design of steel structures with displacement constraints. The dual method can replace a primary optimization problem with a sequence of approximate explicit subproblems with a simple algebraic structure. Since being convex and separable, each subproblem can be solved efficiently by the dual method. Specifically, this study uses the principle of virtual work to obtain the displacement constraint equations with an explicit form and adds the linear regression equation expressing the relationships between the cross-section properties to the dual algorithm to reduce the number of design variables. Furthermore, this study deals with the discrete optimization problem to select members with the standard steel sections. Through numerical analyses, the proposed method will be compared with the conventional optimality criteria method.